{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Riskfolio-Lib Tutorial: \n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 25: Hierarchical Equal Risk Contribution (HERC) Portfolio Optimization\n",
    "\n",
    "## 1. Downloading the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  25 of 25 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "assets.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(assets, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>-2.0257%</td>\n",
       "      <td>0.4057%</td>\n",
       "      <td>0.4036%</td>\n",
       "      <td>1.9693%</td>\n",
       "      <td>0.0179%</td>\n",
       "      <td>0.9305%</td>\n",
       "      <td>0.3678%</td>\n",
       "      <td>0.5783%</td>\n",
       "      <td>0.9483%</td>\n",
       "      <td>-1.1953%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5881%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>2.8236%</td>\n",
       "      <td>0.9758%</td>\n",
       "      <td>0.6987%</td>\n",
       "      <td>1.7539%</td>\n",
       "      <td>-0.1730%</td>\n",
       "      <td>0.2409%</td>\n",
       "      <td>1.3734%</td>\n",
       "      <td>-1.0857%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-11.4863%</td>\n",
       "      <td>-1.5879%</td>\n",
       "      <td>0.2412%</td>\n",
       "      <td>-1.7556%</td>\n",
       "      <td>-0.7727%</td>\n",
       "      <td>-1.2473%</td>\n",
       "      <td>-0.1736%</td>\n",
       "      <td>-1.1239%</td>\n",
       "      <td>-3.5867%</td>\n",
       "      <td>-0.9551%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5548%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>0.1592%</td>\n",
       "      <td>-1.5647%</td>\n",
       "      <td>0.3108%</td>\n",
       "      <td>-1.0155%</td>\n",
       "      <td>-0.7653%</td>\n",
       "      <td>-3.0048%</td>\n",
       "      <td>-0.9034%</td>\n",
       "      <td>-2.9144%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-5.1388%</td>\n",
       "      <td>-4.1922%</td>\n",
       "      <td>-1.6573%</td>\n",
       "      <td>-2.7700%</td>\n",
       "      <td>-1.1047%</td>\n",
       "      <td>-1.9769%</td>\n",
       "      <td>-1.2207%</td>\n",
       "      <td>-0.8856%</td>\n",
       "      <td>-4.6058%</td>\n",
       "      <td>-2.5394%</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.2066%</td>\n",
       "      <td>-3.0309%</td>\n",
       "      <td>-1.0410%</td>\n",
       "      <td>-3.1557%</td>\n",
       "      <td>-1.6148%</td>\n",
       "      <td>-0.2700%</td>\n",
       "      <td>-2.2844%</td>\n",
       "      <td>-2.0570%</td>\n",
       "      <td>-0.5493%</td>\n",
       "      <td>-3.0019%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>0.2736%</td>\n",
       "      <td>-2.2705%</td>\n",
       "      <td>-1.6037%</td>\n",
       "      <td>-2.5425%</td>\n",
       "      <td>0.1099%</td>\n",
       "      <td>-0.2241%</td>\n",
       "      <td>0.5707%</td>\n",
       "      <td>-1.6402%</td>\n",
       "      <td>-1.7642%</td>\n",
       "      <td>-0.1649%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1539%</td>\n",
       "      <td>-1.1366%</td>\n",
       "      <td>-0.7308%</td>\n",
       "      <td>-0.1448%</td>\n",
       "      <td>0.0895%</td>\n",
       "      <td>-3.3839%</td>\n",
       "      <td>-0.1117%</td>\n",
       "      <td>-1.1387%</td>\n",
       "      <td>-0.9719%</td>\n",
       "      <td>-1.1254%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>-4.3383%</td>\n",
       "      <td>0.1692%</td>\n",
       "      <td>-1.6851%</td>\n",
       "      <td>-1.0215%</td>\n",
       "      <td>0.0915%</td>\n",
       "      <td>-1.1791%</td>\n",
       "      <td>0.5674%</td>\n",
       "      <td>0.5287%</td>\n",
       "      <td>0.6616%</td>\n",
       "      <td>0.0330%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6436%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9869%</td>\n",
       "      <td>-0.1451%</td>\n",
       "      <td>1.2224%</td>\n",
       "      <td>1.4570%</td>\n",
       "      <td>0.5367%</td>\n",
       "      <td>-0.4607%</td>\n",
       "      <td>0.5799%</td>\n",
       "      <td>-1.9919%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 APA       BA      BAX      BMY    CMCSA      CNP      CPB  \\\n",
       "Date                                                                         \n",
       "2016-01-05  -2.0257%  0.4057%  0.4036%  1.9693%  0.0179%  0.9305%  0.3678%   \n",
       "2016-01-06 -11.4863% -1.5879%  0.2412% -1.7556% -0.7727% -1.2473% -0.1736%   \n",
       "2016-01-07  -5.1388% -4.1922% -1.6573% -2.7700% -1.1047% -1.9769% -1.2207%   \n",
       "2016-01-08   0.2736% -2.2705% -1.6037% -2.5425%  0.1099% -0.2241%  0.5707%   \n",
       "2016-01-11  -4.3383%  0.1692% -1.6851% -1.0215%  0.0915% -1.1791%  0.5674%   \n",
       "\n",
       "                 DE      HPQ      JCI  ...       NI     PCAR      PSA  \\\n",
       "Date                                   ...                              \n",
       "2016-01-05  0.5783%  0.9483% -1.1953%  ...  1.5881%  0.0212%  2.8236%   \n",
       "2016-01-06 -1.1239% -3.5867% -0.9551%  ...  0.5548%  0.0212%  0.1592%   \n",
       "2016-01-07 -0.8856% -4.6058% -2.5394%  ... -2.2066% -3.0309% -1.0410%   \n",
       "2016-01-08 -1.6402% -1.7642% -0.1649%  ... -0.1539% -1.1366% -0.7308%   \n",
       "2016-01-11  0.5287%  0.6616%  0.0330%  ...  1.6436%  0.0000%  0.9869%   \n",
       "\n",
       "                SEE        T      TGT      TMO      TXT       VZ     ZION  \n",
       "Date                                                                       \n",
       "2016-01-05  0.9758%  0.6987%  1.7539% -0.1730%  0.2409%  1.3734% -1.0857%  \n",
       "2016-01-06 -1.5647%  0.3108% -1.0155% -0.7653% -3.0048% -0.9034% -2.9144%  \n",
       "2016-01-07 -3.1557% -1.6148% -0.2700% -2.2844% -2.0570% -0.5493% -3.0019%  \n",
       "2016-01-08 -0.1448%  0.0895% -3.3839% -0.1117% -1.1387% -0.9719% -1.1254%  \n",
       "2016-01-11 -0.1451%  1.2224%  1.4570%  0.5367% -0.4607%  0.5799% -1.9919%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating returns\n",
    "\n",
    "Y = data[assets].pct_change().dropna()\n",
    "\n",
    "display(Y.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio as rp\n",
    "\n",
    "# Plotting Assets Clusters\n",
    "\n",
    "ax = rp.plot_clusters(returns=Y,\n",
    "                      codependence='pearson',\n",
    "                      linkage='ward',\n",
    "                      k=None,\n",
    "                      max_k=10,\n",
    "                      leaf_order=True,\n",
    "                      dendrogram=True,\n",
    "                      #linecolor='tab:purple',\n",
    "                      ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The graph above suggest that optimal number of clusters are four.\n",
    "\n",
    "## 2. Estimating HERC Portfolio\n",
    "\n",
    "This is the original model proposed by Raffinot (2018). Riskfolio-Lib expand this model to 32 risk measures.\n",
    "\n",
    "### 2.1 Calculating the HERC portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.6423%</td>\n",
       "      <td>1.7311%</td>\n",
       "      <td>4.5531%</td>\n",
       "      <td>2.6465%</td>\n",
       "      <td>5.8394%</td>\n",
       "      <td>7.6405%</td>\n",
       "      <td>3.9025%</td>\n",
       "      <td>1.7334%</td>\n",
       "      <td>2.2530%</td>\n",
       "      <td>2.2505%</td>\n",
       "      <td>...</td>\n",
       "      <td>7.3687%</td>\n",
       "      <td>2.1231%</td>\n",
       "      <td>6.9433%</td>\n",
       "      <td>2.0169%</td>\n",
       "      <td>7.7390%</td>\n",
       "      <td>3.1855%</td>\n",
       "      <td>4.0472%</td>\n",
       "      <td>1.8479%</td>\n",
       "      <td>8.7857%</td>\n",
       "      <td>1.6270%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA     BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.6423% 1.7311% 4.5531% 2.6465% 5.8394% 7.6405% 3.9025% 1.7334%   \n",
       "\n",
       "            HPQ     JCI  ...      NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 2.2530% 2.2505%  ... 7.3687% 2.1231% 6.9433% 2.0169% 7.7390% 3.1855%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 4.0472% 1.8479% 8.7857% 1.6270%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Building the portfolio object\n",
    "port = rp.HCPortfolio(returns=Y)\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "model='HERC' # Could be HRP or HERC\n",
    "codependence = 'pearson' # Correlation matrix used to group assets in clusters\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "rf = 0 # Risk free rate\n",
    "linkage = 'ward' # Linkage method used to build clusters\n",
    "max_k = 10 # Max number of clusters used in two difference gap statistic\n",
    "leaf_order = True # Consider optimal order of leafs in dendrogram\n",
    "\n",
    "w = port.optimization(model=model,\n",
    "                      codependence=codependence,\n",
    "                      rm=rm,\n",
    "                      rf=rf,\n",
    "                      linkage=linkage,\n",
    "                      max_k=max_k,\n",
    "                      leaf_order=leaf_order)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = rp.plot_pie(w=w,\n",
    "                 title='HERC Naive Risk Parity',\n",
    "                 others=0.05,\n",
    "                 nrow=25,\n",
    "                 cmap=\"tab20\",\n",
    "                 height=8,\n",
    "                 width=10,\n",
    "                 ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Plotting Risk Contribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the risk contribution per asset\n",
    "\n",
    "mu = Y.mean()\n",
    "cov = Y.cov() # Covariance matrix\n",
    "returns = Y # Returns of the assets\n",
    "\n",
    "ax = rp.plot_risk_con(w=w,\n",
    "                      cov=cov,\n",
    "                      returns=returns,\n",
    "                      rm=rm,\n",
    "                      rf=0,\n",
    "                      alpha=0.05,\n",
    "                      color=\"tab:blue\",\n",
    "                      height=6,\n",
    "                      width=10,\n",
    "                      t_factor=252,\n",
    "                      ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4 Calculate Optimal HERC Portfolios for Several Risk Measures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Risk Measures available:\n",
    "#\n",
    "# 'vol': Standard Deviation.\n",
    "# 'MV': Variance.\n",
    "# 'MAD': Mean Absolute Deviation.\n",
    "# 'GMD': Gini Mean Difference.\n",
    "# 'MSV': Semi Standard Deviation.\n",
    "# 'FLPM': First Lower Partial Moment (Omega Ratio).\n",
    "# 'SLPM': Second Lower Partial Moment (Sortino Ratio).\n",
    "# 'VaR': Conditional Value at Risk.\n",
    "# 'CVaR': Conditional Value at Risk.\n",
    "# 'TG': Tail Gini.\n",
    "# 'EVaR': Entropic Value at Risk.\n",
    "# 'WR': Worst Realization (Minimax).\n",
    "# 'RG': Range of returns.\n",
    "# 'CVRG': CVaR Range of returns.\n",
    "# 'TGRG': Tail Gini Range of returns.\n",
    "# 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD': Average Drawdown of uncompounded cumulative returns.\n",
    "# 'DaR': Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'UCI': Ulcer Index of uncompounded cumulative returns.\n",
    "# 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD_Rel': Average Drawdown of compounded cumulative returns.\n",
    "# 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.\n",
    "# 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.\n",
    "# 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.\n",
    "# 'UCI_Rel': Ulcer Index of compounded cumulative returns.\n",
    "\n",
    "rms = ['vol', 'MV', 'MAD', 'GMD', 'MSV', 'FLPM', 'SLPM', 'VaR',\n",
    "       'CVaR', 'TG', 'EVaR', 'WR', 'RG', 'CVRG', 'TGRG', 'MDD', \n",
    "       'ADD', 'DaR', 'CDaR', 'EDaR', 'UCI', 'MDD_Rel',\n",
    "       'ADD_Rel', 'DaR_Rel', 'CDaR_Rel', 'EDaR_Rel', 'UCI_Rel']\n",
    "\n",
    "w_s = pd.DataFrame([])\n",
    "\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model,\n",
    "                          codependence=codependence,\n",
    "                          rm=i,\n",
    "                          rf=rf,\n",
    "                          linkage=linkage,\n",
    "                          max_k=max_k,\n",
    "                          leaf_order=leaf_order)\n",
    "\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "#T_1c241_row4_col15 {\n",
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       "#T_1c241_row4_col24, #T_1c241_row6_col3 {\n",
       "  background-color: #5fba6c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row4_col25, #T_1c241_row13_col3, #T_1c241_row19_col21 {\n",
       "  background-color: #369d54;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col0, #T_1c241_row15_col9 {\n",
       "  background-color: #177b3f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col1, #T_1c241_row19_col4 {\n",
       "  background-color: #056c39;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col2, #T_1c241_row14_col24 {\n",
       "  background-color: #218242;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col3, #T_1c241_row12_col5, #T_1c241_row15_col7, #T_1c241_row15_col24, #T_1c241_row17_col11 {\n",
       "  background-color: #1e8041;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col4, #T_1c241_row5_col6, #T_1c241_row14_col18, #T_1c241_row19_col12 {\n",
       "  background-color: #167a3f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col5, #T_1c241_row15_col2, #T_1c241_row15_col18, #T_1c241_row19_col9 {\n",
       "  background-color: #208242;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col7, #T_1c241_row12_col7 {\n",
       "  background-color: #298c48;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col8, #T_1c241_row5_col18, #T_1c241_row23_col24 {\n",
       "  background-color: #0a703a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col9, #T_1c241_row15_col14 {\n",
       "  background-color: #086e3a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col10 {\n",
       "  background-color: #005b32;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col11, #T_1c241_row19_col14 {\n",
       "  background-color: #006636;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col12, #T_1c241_row15_col19 {\n",
       "  background-color: #004a2b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col13, #T_1c241_row5_col24, #T_1c241_row19_col19 {\n",
       "  background-color: #0b713b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col14 {\n",
       "  background-color: #066d39;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col15 {\n",
       "  background-color: #00512e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col16, #T_1c241_row15_col4, #T_1c241_row17_col0, #T_1c241_row17_col8, #T_1c241_row17_col9, #T_1c241_row21_col18 {\n",
       "  background-color: #248644;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col17, #T_1c241_row5_col23 {\n",
       "  background-color: #30954f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col19, #T_1c241_row12_col16, #T_1c241_row12_col17, #T_1c241_row12_col18, #T_1c241_row12_col20, #T_1c241_row12_col22, #T_1c241_row12_col23, #T_1c241_row12_col24, #T_1c241_row12_col26, #T_1c241_row15_col15, #T_1c241_row15_col21, #T_1c241_row17_col12, #T_1c241_row23_col0, #T_1c241_row23_col1, #T_1c241_row23_col2, #T_1c241_row23_col3, #T_1c241_row23_col4, #T_1c241_row23_col5, #T_1c241_row23_col6, #T_1c241_row23_col7, #T_1c241_row23_col8, #T_1c241_row23_col9, #T_1c241_row23_col10, #T_1c241_row23_col11, #T_1c241_row23_col13, #T_1c241_row23_col14, #T_1c241_row23_col19, #T_1c241_row23_col25 {\n",
       "  background-color: #004529;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col21 {\n",
       "  background-color: #00532f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col22, #T_1c241_row19_col18 {\n",
       "  background-color: #288a47;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row5_col25 {\n",
       "  background-color: #004d2c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row6_col0, #T_1c241_row21_col5 {\n",
       "  background-color: #75c578;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col2 {\n",
       "  background-color: #5ab76a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row6_col4, #T_1c241_row20_col9 {\n",
       "  background-color: #74c477;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col5, #T_1c241_row15_col22, #T_1c241_row21_col21 {\n",
       "  background-color: #69bf72;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col7 {\n",
       "  background-color: #4fb264;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row6_col11, #T_1c241_row10_col5 {\n",
       "  background-color: #d2eda0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col13, #T_1c241_row13_col12, #T_1c241_row15_col17 {\n",
       "  background-color: #72c376;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col15, #T_1c241_row13_col24 {\n",
       "  background-color: #cbea9c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col16, #T_1c241_row6_col22, #T_1c241_row7_col8, #T_1c241_row7_col11, #T_1c241_row8_col10, #T_1c241_row9_col21, #T_1c241_row9_col22, #T_1c241_row16_col11, #T_1c241_row24_col4, #T_1c241_row24_col7 {\n",
       "  background-color: #f8fdc1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col21, #T_1c241_row10_col18 {\n",
       "  background-color: #bde496;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row6_col24, #T_1c241_row8_col16, #T_1c241_row8_col25, #T_1c241_row10_col6, #T_1c241_row20_col12 {\n",
       "  background-color: #def2a7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col3, #T_1c241_row9_col9, #T_1c241_row9_col17, #T_1c241_row16_col24, #T_1c241_row18_col13 {\n",
       "  background-color: #f1fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col12, #T_1c241_row18_col22, #T_1c241_row22_col17, #T_1c241_row24_col10 {\n",
       "  background-color: #fbfed0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col13, #T_1c241_row11_col0, #T_1c241_row11_col1, #T_1c241_row11_col15, #T_1c241_row24_col24 {\n",
       "  background-color: #f7fcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col15, #T_1c241_row8_col18 {\n",
       "  background-color: #ddf1a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col21, #T_1c241_row8_col15, #T_1c241_row10_col13, #T_1c241_row13_col17, #T_1c241_row13_col23, #T_1c241_row17_col16 {\n",
       "  background-color: #e5f5ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col22, #T_1c241_row7_col24, #T_1c241_row7_col26, #T_1c241_row8_col9, #T_1c241_row8_col20, #T_1c241_row8_col22, #T_1c241_row8_col24, #T_1c241_row10_col7 {\n",
       "  background-color: #e0f3a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row7_col25, #T_1c241_row20_col17 {\n",
       "  background-color: #dbf1a4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row8_col0 {\n",
       "  background-color: #ccea9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row8_col2 {\n",
       "  background-color: #bce395;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row8_col3, #T_1c241_row10_col16, #T_1c241_row10_col25, #T_1c241_row10_col26 {\n",
       "  background-color: #c3e698;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row8_col6, #T_1c241_row8_col14, #T_1c241_row17_col20 {\n",
       "  background-color: #d5eea1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row8_col11, #T_1c241_row18_col21, #T_1c241_row22_col9, #T_1c241_row22_col25 {\n",
       "  background-color: #fafdcb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row9_col7, #T_1c241_row9_col18, #T_1c241_row16_col13, #T_1c241_row16_col14, #T_1c241_row16_col17, #T_1c241_row16_col25, #T_1c241_row22_col3, #T_1c241_row22_col5 {\n",
       "  background-color: #eef9b3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row9_col8, #T_1c241_row16_col4, #T_1c241_row16_col7, #T_1c241_row16_col26, #T_1c241_row18_col7 {\n",
       "  background-color: #f0f9b4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row9_col15, #T_1c241_row16_col10, #T_1c241_row24_col0, #T_1c241_row24_col1, #T_1c241_row24_col2, #T_1c241_row24_col3, #T_1c241_row24_col14, #T_1c241_row24_col16, #T_1c241_row24_col23, #T_1c241_row24_col26 {\n",
       "  background-color: #f7fcbc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row9_col25, #T_1c241_row10_col12, #T_1c241_row11_col24, #T_1c241_row22_col13 {\n",
       "  background-color: #f4fbb7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col0, #T_1c241_row10_col4, #T_1c241_row10_col15 {\n",
       "  background-color: #e1f3a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col2, #T_1c241_row20_col22 {\n",
       "  background-color: #dcf1a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col17 {\n",
       "  background-color: #b8e293;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col21 {\n",
       "  background-color: #e2f4aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col22 {\n",
       "  background-color: #c5e89a;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row10_col24, #T_1c241_row17_col17, #T_1c241_row17_col23 {\n",
       "  background-color: #c1e698;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row11_col4, #T_1c241_row11_col6, #T_1c241_row11_col20, #T_1c241_row18_col8, #T_1c241_row18_col18, #T_1c241_row24_col6, #T_1c241_row24_col15, #T_1c241_row24_col21 {\n",
       "  background-color: #f8fcc0;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row11_col10 {\n",
       "  background-color: #fdfed9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row11_col11 {\n",
       "  background-color: #fdfedd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row11_col22, #T_1c241_row18_col11, #T_1c241_row22_col12, #T_1c241_row22_col15, #T_1c241_row22_col16, #T_1c241_row22_col22 {\n",
       "  background-color: #fafdcc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row11_col26, #T_1c241_row18_col16, #T_1c241_row18_col23 {\n",
       "  background-color: #f9fdc5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row12_col0, #T_1c241_row12_col4, #T_1c241_row13_col2, #T_1c241_row13_col13, #T_1c241_row20_col7 {\n",
       "  background-color: #349a52;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col1, #T_1c241_row19_col8 {\n",
       "  background-color: #12763d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col2, #T_1c241_row17_col2 {\n",
       "  background-color: #2b8e4a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col3, #T_1c241_row19_col15 {\n",
       "  background-color: #2f944e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col6 {\n",
       "  background-color: #2f934d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col8 {\n",
       "  background-color: #3ca458;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col9, #T_1c241_row20_col2, #T_1c241_row21_col17 {\n",
       "  background-color: #40aa5c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col10, #T_1c241_row17_col3 {\n",
       "  background-color: #2a8d49;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col11 {\n",
       "  background-color: #2e924c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col12 {\n",
       "  background-color: #51b365;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col14, #T_1c241_row13_col1, #T_1c241_row13_col4, #T_1c241_row19_col10, #T_1c241_row23_col17 {\n",
       "  background-color: #3fa95c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col15, #T_1c241_row13_col9 {\n",
       "  background-color: #4cb063;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col19 {\n",
       "  background-color: #006034;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col21, #T_1c241_row23_col20 {\n",
       "  background-color: #45ad5f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row12_col25 {\n",
       "  background-color: #005f34;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col0, #T_1c241_row14_col23, #T_1c241_row17_col5, #T_1c241_row21_col26 {\n",
       "  background-color: #389f55;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col5, #T_1c241_row21_col22 {\n",
       "  background-color: #3fa85b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col6, #T_1c241_row20_col3 {\n",
       "  background-color: #49af61;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col8 {\n",
       "  background-color: #43ac5e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col14, #T_1c241_row19_col24 {\n",
       "  background-color: #339951;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row13_col15, #T_1c241_row14_col11 {\n",
       "  background-color: #a9db8c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row13_col18 {\n",
       "  background-color: #ceeb9e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row13_col19 {\n",
       "  background-color: #b1df90;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row13_col25, #T_1c241_row20_col24 {\n",
       "  background-color: #aedd8e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col2 {\n",
       "  background-color: #86cc7f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col3 {\n",
       "  background-color: #90d083;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col7 {\n",
       "  background-color: #92d183;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col12 {\n",
       "  background-color: #afde8f;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col14 {\n",
       "  background-color: #a7db8c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row14_col16 {\n",
       "  background-color: #005730;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row14_col17, #T_1c241_row21_col20 {\n",
       "  background-color: #359c53;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row14_col20, #T_1c241_row15_col13, #T_1c241_row19_col6, #T_1c241_row23_col12 {\n",
       "  background-color: #076d39;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row14_col22 {\n",
       "  background-color: #006335;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row14_col25, #T_1c241_row17_col7, #T_1c241_row21_col25 {\n",
       "  background-color: #268846;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row14_col26, #T_1c241_row17_col10 {\n",
       "  background-color: #13773d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row15_col1, #T_1c241_row15_col8 {\n",
       "  background-color: #0d733c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row15_col5 {\n",
       "  background-color: #228343;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row15_col6 {\n",
       "  background-color: #278946;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row15_col10 {\n",
       "  background-color: #9fd788;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row15_col16, #T_1c241_row15_col23, #T_1c241_row20_col13 {\n",
       "  background-color: #6bc072;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row15_col25 {\n",
       "  background-color: #00502d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row17_col4, #T_1c241_row21_col19, #T_1c241_row21_col24 {\n",
       "  background-color: #258745;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row17_col6 {\n",
       "  background-color: #2d914b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row17_col14 {\n",
       "  background-color: #14783e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row17_col18, #T_1c241_row17_col24, #T_1c241_row20_col14, #T_1c241_row21_col2 {\n",
       "  background-color: #83cb7d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row17_col19 {\n",
       "  background-color: #4ab062;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row17_col26, #T_1c241_row20_col20 {\n",
       "  background-color: #d9f0a3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row19_col0, #T_1c241_row23_col15 {\n",
       "  background-color: #005931;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col1 {\n",
       "  background-color: #006837;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col2 {\n",
       "  background-color: #004c2c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col3, #T_1c241_row19_col5 {\n",
       "  background-color: #004f2d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col7 {\n",
       "  background-color: #00482a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col13 {\n",
       "  background-color: #005e33;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row19_col16 {\n",
       "  background-color: #93d284;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row19_col17 {\n",
       "  background-color: #64bc6f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row20_col1 {\n",
       "  background-color: #c4e799;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row20_col4, #T_1c241_row20_col8 {\n",
       "  background-color: #5db96b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row20_col6 {\n",
       "  background-color: #5cb86b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row20_col10 {\n",
       "  background-color: #b5e092;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row20_col11 {\n",
       "  background-color: #c8e99b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row20_col18 {\n",
       "  background-color: #b9e294;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row20_col19, #T_1c241_row21_col14 {\n",
       "  background-color: #97d385;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row21_col0 {\n",
       "  background-color: #8bce81;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row21_col1, #T_1c241_row21_col8 {\n",
       "  background-color: #9ad587;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row21_col9 {\n",
       "  background-color: #9cd687;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row21_col16, #T_1c241_row23_col23 {\n",
       "  background-color: #3aa257;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row22_col10 {\n",
       "  background-color: #ffffe4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row22_col20, #T_1c241_row22_col24, #T_1c241_row22_col26 {\n",
       "  background-color: #fbfdcf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row22_col23 {\n",
       "  background-color: #fbfed2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_1c241_row23_col18 {\n",
       "  background-color: #10743c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row23_col21 {\n",
       "  background-color: #00542f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row23_col26 {\n",
       "  background-color: #42ab5d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_1c241_row24_col11 {\n",
       "  background-color: #fcfed6;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_1c241\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_1c241_level0_col0\" class=\"col_heading level0 col0\" >vol</th>\n",
       "      <th id=\"T_1c241_level0_col1\" class=\"col_heading level0 col1\" >MV</th>\n",
       "      <th id=\"T_1c241_level0_col2\" class=\"col_heading level0 col2\" >MAD</th>\n",
       "      <th id=\"T_1c241_level0_col3\" class=\"col_heading level0 col3\" >GMD</th>\n",
       "      <th id=\"T_1c241_level0_col4\" class=\"col_heading level0 col4\" >MSV</th>\n",
       "      <th id=\"T_1c241_level0_col5\" class=\"col_heading level0 col5\" >FLPM</th>\n",
       "      <th id=\"T_1c241_level0_col6\" class=\"col_heading level0 col6\" >SLPM</th>\n",
       "      <th id=\"T_1c241_level0_col7\" class=\"col_heading level0 col7\" >VaR</th>\n",
       "      <th id=\"T_1c241_level0_col8\" class=\"col_heading level0 col8\" >CVaR</th>\n",
       "      <th id=\"T_1c241_level0_col9\" class=\"col_heading level0 col9\" >TG</th>\n",
       "      <th id=\"T_1c241_level0_col10\" class=\"col_heading level0 col10\" >EVaR</th>\n",
       "      <th id=\"T_1c241_level0_col11\" class=\"col_heading level0 col11\" >WR</th>\n",
       "      <th id=\"T_1c241_level0_col12\" class=\"col_heading level0 col12\" >RG</th>\n",
       "      <th id=\"T_1c241_level0_col13\" class=\"col_heading level0 col13\" >CVRG</th>\n",
       "      <th id=\"T_1c241_level0_col14\" class=\"col_heading level0 col14\" >TGRG</th>\n",
       "      <th id=\"T_1c241_level0_col15\" class=\"col_heading level0 col15\" >MDD</th>\n",
       "      <th id=\"T_1c241_level0_col16\" class=\"col_heading level0 col16\" >ADD</th>\n",
       "      <th id=\"T_1c241_level0_col17\" class=\"col_heading level0 col17\" >DaR</th>\n",
       "      <th id=\"T_1c241_level0_col18\" class=\"col_heading level0 col18\" >CDaR</th>\n",
       "      <th id=\"T_1c241_level0_col19\" class=\"col_heading level0 col19\" >EDaR</th>\n",
       "      <th id=\"T_1c241_level0_col20\" class=\"col_heading level0 col20\" >UCI</th>\n",
       "      <th id=\"T_1c241_level0_col21\" class=\"col_heading level0 col21\" >MDD_Rel</th>\n",
       "      <th id=\"T_1c241_level0_col22\" class=\"col_heading level0 col22\" >ADD_Rel</th>\n",
       "      <th id=\"T_1c241_level0_col23\" class=\"col_heading level0 col23\" >DaR_Rel</th>\n",
       "      <th id=\"T_1c241_level0_col24\" class=\"col_heading level0 col24\" >CDaR_Rel</th>\n",
       "      <th id=\"T_1c241_level0_col25\" class=\"col_heading level0 col25\" >EDaR_Rel</th>\n",
       "      <th id=\"T_1c241_level0_col26\" class=\"col_heading level0 col26\" >UCI_Rel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_1c241_row0_col0\" class=\"data row0 col0\" >1.29%</td>\n",
       "      <td id=\"T_1c241_row0_col1\" class=\"data row0 col1\" >0.64%</td>\n",
       "      <td id=\"T_1c241_row0_col2\" class=\"data row0 col2\" >1.28%</td>\n",
       "      <td id=\"T_1c241_row0_col3\" class=\"data row0 col3\" >1.28%</td>\n",
       "      <td id=\"T_1c241_row0_col4\" class=\"data row0 col4\" >1.34%</td>\n",
       "      <td id=\"T_1c241_row0_col5\" class=\"data row0 col5\" >1.20%</td>\n",
       "      <td id=\"T_1c241_row0_col6\" class=\"data row0 col6\" >1.29%</td>\n",
       "      <td id=\"T_1c241_row0_col7\" class=\"data row0 col7\" >1.21%</td>\n",
       "      <td id=\"T_1c241_row0_col8\" class=\"data row0 col8\" >1.35%</td>\n",
       "      <td id=\"T_1c241_row0_col9\" class=\"data row0 col9\" >1.39%</td>\n",
       "      <td id=\"T_1c241_row0_col10\" class=\"data row0 col10\" >1.39%</td>\n",
       "      <td id=\"T_1c241_row0_col11\" class=\"data row0 col11\" >1.37%</td>\n",
       "      <td id=\"T_1c241_row0_col12\" class=\"data row0 col12\" >1.17%</td>\n",
       "      <td id=\"T_1c241_row0_col13\" class=\"data row0 col13\" >1.29%</td>\n",
       "      <td id=\"T_1c241_row0_col14\" class=\"data row0 col14\" >1.30%</td>\n",
       "      <td id=\"T_1c241_row0_col15\" class=\"data row0 col15\" >0.61%</td>\n",
       "      <td id=\"T_1c241_row0_col16\" class=\"data row0 col16\" >0.45%</td>\n",
       "      <td id=\"T_1c241_row0_col17\" class=\"data row0 col17\" >0.60%</td>\n",
       "      <td id=\"T_1c241_row0_col18\" class=\"data row0 col18\" >0.58%</td>\n",
       "      <td id=\"T_1c241_row0_col19\" class=\"data row0 col19\" >0.59%</td>\n",
       "      <td id=\"T_1c241_row0_col20\" class=\"data row0 col20\" >0.52%</td>\n",
       "      <td id=\"T_1c241_row0_col21\" class=\"data row0 col21\" >0.80%</td>\n",
       "      <td id=\"T_1c241_row0_col22\" class=\"data row0 col22\" >0.53%</td>\n",
       "      <td id=\"T_1c241_row0_col23\" class=\"data row0 col23\" >0.75%</td>\n",
       "      <td id=\"T_1c241_row0_col24\" class=\"data row0 col24\" >0.74%</td>\n",
       "      <td id=\"T_1c241_row0_col25\" class=\"data row0 col25\" >0.77%</td>\n",
       "      <td id=\"T_1c241_row0_col26\" class=\"data row0 col26\" >0.61%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_1c241_row1_col0\" class=\"data row1 col0\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row1_col1\" class=\"data row1 col1\" >1.73%</td>\n",
       "      <td id=\"T_1c241_row1_col2\" class=\"data row1 col2\" >2.17%</td>\n",
       "      <td id=\"T_1c241_row1_col3\" class=\"data row1 col3\" >2.14%</td>\n",
       "      <td id=\"T_1c241_row1_col4\" class=\"data row1 col4\" >2.09%</td>\n",
       "      <td id=\"T_1c241_row1_col5\" class=\"data row1 col5\" >2.23%</td>\n",
       "      <td id=\"T_1c241_row1_col6\" class=\"data row1 col6\" >2.11%</td>\n",
       "      <td id=\"T_1c241_row1_col7\" class=\"data row1 col7\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row1_col8\" class=\"data row1 col8\" >1.97%</td>\n",
       "      <td id=\"T_1c241_row1_col9\" class=\"data row1 col9\" >1.96%</td>\n",
       "      <td id=\"T_1c241_row1_col10\" class=\"data row1 col10\" >2.01%</td>\n",
       "      <td id=\"T_1c241_row1_col11\" class=\"data row1 col11\" >1.89%</td>\n",
       "      <td id=\"T_1c241_row1_col12\" class=\"data row1 col12\" >1.85%</td>\n",
       "      <td id=\"T_1c241_row1_col13\" class=\"data row1 col13\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row1_col14\" class=\"data row1 col14\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row1_col15\" class=\"data row1 col15\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row1_col16\" class=\"data row1 col16\" >2.36%</td>\n",
       "      <td id=\"T_1c241_row1_col17\" class=\"data row1 col17\" >2.34%</td>\n",
       "      <td id=\"T_1c241_row1_col18\" class=\"data row1 col18\" >2.16%</td>\n",
       "      <td id=\"T_1c241_row1_col19\" class=\"data row1 col19\" >2.20%</td>\n",
       "      <td id=\"T_1c241_row1_col20\" class=\"data row1 col20\" >2.29%</td>\n",
       "      <td id=\"T_1c241_row1_col21\" class=\"data row1 col21\" >2.13%</td>\n",
       "      <td id=\"T_1c241_row1_col22\" class=\"data row1 col22\" >2.33%</td>\n",
       "      <td id=\"T_1c241_row1_col23\" class=\"data row1 col23\" >2.32%</td>\n",
       "      <td id=\"T_1c241_row1_col24\" class=\"data row1 col24\" >2.15%</td>\n",
       "      <td id=\"T_1c241_row1_col25\" class=\"data row1 col25\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row1_col26\" class=\"data row1 col26\" >2.28%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_1c241_row2_col0\" class=\"data row2 col0\" >4.41%</td>\n",
       "      <td id=\"T_1c241_row2_col1\" class=\"data row2 col1\" >4.55%</td>\n",
       "      <td id=\"T_1c241_row2_col2\" class=\"data row2 col2\" >4.52%</td>\n",
       "      <td id=\"T_1c241_row2_col3\" class=\"data row2 col3\" >4.47%</td>\n",
       "      <td id=\"T_1c241_row2_col4\" class=\"data row2 col4\" >4.23%</td>\n",
       "      <td id=\"T_1c241_row2_col5\" class=\"data row2 col5\" >4.71%</td>\n",
       "      <td id=\"T_1c241_row2_col6\" class=\"data row2 col6\" >4.30%</td>\n",
       "      <td id=\"T_1c241_row2_col7\" class=\"data row2 col7\" >4.31%</td>\n",
       "      <td id=\"T_1c241_row2_col8\" class=\"data row2 col8\" >4.15%</td>\n",
       "      <td id=\"T_1c241_row2_col9\" class=\"data row2 col9\" >4.08%</td>\n",
       "      <td id=\"T_1c241_row2_col10\" class=\"data row2 col10\" >3.53%</td>\n",
       "      <td id=\"T_1c241_row2_col11\" class=\"data row2 col11\" >3.34%</td>\n",
       "      <td id=\"T_1c241_row2_col12\" class=\"data row2 col12\" >3.91%</td>\n",
       "      <td id=\"T_1c241_row2_col13\" class=\"data row2 col13\" >4.33%</td>\n",
       "      <td id=\"T_1c241_row2_col14\" class=\"data row2 col14\" >4.33%</td>\n",
       "      <td id=\"T_1c241_row2_col15\" class=\"data row2 col15\" >4.27%</td>\n",
       "      <td id=\"T_1c241_row2_col16\" class=\"data row2 col16\" >6.60%</td>\n",
       "      <td id=\"T_1c241_row2_col17\" class=\"data row2 col17\" >5.30%</td>\n",
       "      <td id=\"T_1c241_row2_col18\" class=\"data row2 col18\" >4.87%</td>\n",
       "      <td id=\"T_1c241_row2_col19\" class=\"data row2 col19\" >4.55%</td>\n",
       "      <td id=\"T_1c241_row2_col20\" class=\"data row2 col20\" >5.96%</td>\n",
       "      <td id=\"T_1c241_row2_col21\" class=\"data row2 col21\" >4.33%</td>\n",
       "      <td id=\"T_1c241_row2_col22\" class=\"data row2 col22\" >6.69%</td>\n",
       "      <td id=\"T_1c241_row2_col23\" class=\"data row2 col23\" >5.33%</td>\n",
       "      <td id=\"T_1c241_row2_col24\" class=\"data row2 col24\" >4.88%</td>\n",
       "      <td id=\"T_1c241_row2_col25\" class=\"data row2 col25\" >4.59%</td>\n",
       "      <td id=\"T_1c241_row2_col26\" class=\"data row2 col26\" >6.06%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_1c241_row3_col0\" class=\"data row3 col0\" >3.36%</td>\n",
       "      <td id=\"T_1c241_row3_col1\" class=\"data row3 col1\" >2.65%</td>\n",
       "      <td id=\"T_1c241_row3_col2\" class=\"data row3 col2\" >3.67%</td>\n",
       "      <td id=\"T_1c241_row3_col3\" class=\"data row3 col3\" >3.62%</td>\n",
       "      <td id=\"T_1c241_row3_col4\" class=\"data row3 col4\" >3.10%</td>\n",
       "      <td id=\"T_1c241_row3_col5\" class=\"data row3 col5\" >3.51%</td>\n",
       "      <td id=\"T_1c241_row3_col6\" class=\"data row3 col6\" >3.04%</td>\n",
       "      <td id=\"T_1c241_row3_col7\" class=\"data row3 col7\" >3.70%</td>\n",
       "      <td id=\"T_1c241_row3_col8\" class=\"data row3 col8\" >3.04%</td>\n",
       "      <td id=\"T_1c241_row3_col9\" class=\"data row3 col9\" >2.78%</td>\n",
       "      <td id=\"T_1c241_row3_col10\" class=\"data row3 col10\" >2.24%</td>\n",
       "      <td id=\"T_1c241_row3_col11\" class=\"data row3 col11\" >2.11%</td>\n",
       "      <td id=\"T_1c241_row3_col12\" class=\"data row3 col12\" >2.74%</td>\n",
       "      <td id=\"T_1c241_row3_col13\" class=\"data row3 col13\" >3.35%</td>\n",
       "      <td id=\"T_1c241_row3_col14\" class=\"data row3 col14\" >3.19%</td>\n",
       "      <td id=\"T_1c241_row3_col15\" class=\"data row3 col15\" >2.21%</td>\n",
       "      <td id=\"T_1c241_row3_col16\" class=\"data row3 col16\" >1.39%</td>\n",
       "      <td id=\"T_1c241_row3_col17\" class=\"data row3 col17\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row3_col18\" class=\"data row3 col18\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row3_col19\" class=\"data row3 col19\" >2.16%</td>\n",
       "      <td id=\"T_1c241_row3_col20\" class=\"data row3 col20\" >1.62%</td>\n",
       "      <td id=\"T_1c241_row3_col21\" class=\"data row3 col21\" >2.30%</td>\n",
       "      <td id=\"T_1c241_row3_col22\" class=\"data row3 col22\" >1.26%</td>\n",
       "      <td id=\"T_1c241_row3_col23\" class=\"data row3 col23\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row3_col24\" class=\"data row3 col24\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row3_col25\" class=\"data row3 col25\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row3_col26\" class=\"data row3 col26\" >1.51%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_1c241_row4_col0\" class=\"data row4 col0\" >6.20%</td>\n",
       "      <td id=\"T_1c241_row4_col1\" class=\"data row4 col1\" >5.84%</td>\n",
       "      <td id=\"T_1c241_row4_col2\" class=\"data row4 col2\" >5.98%</td>\n",
       "      <td id=\"T_1c241_row4_col3\" class=\"data row4 col3\" >6.03%</td>\n",
       "      <td id=\"T_1c241_row4_col4\" class=\"data row4 col4\" >6.27%</td>\n",
       "      <td id=\"T_1c241_row4_col5\" class=\"data row4 col5\" >6.02%</td>\n",
       "      <td id=\"T_1c241_row4_col6\" class=\"data row4 col6\" >6.31%</td>\n",
       "      <td id=\"T_1c241_row4_col7\" class=\"data row4 col7\" >6.47%</td>\n",
       "      <td id=\"T_1c241_row4_col8\" class=\"data row4 col8\" >6.44%</td>\n",
       "      <td id=\"T_1c241_row4_col9\" class=\"data row4 col9\" >6.43%</td>\n",
       "      <td id=\"T_1c241_row4_col10\" class=\"data row4 col10\" >6.46%</td>\n",
       "      <td id=\"T_1c241_row4_col11\" class=\"data row4 col11\" >6.46%</td>\n",
       "      <td id=\"T_1c241_row4_col12\" class=\"data row4 col12\" >7.27%</td>\n",
       "      <td id=\"T_1c241_row4_col13\" class=\"data row4 col13\" >6.22%</td>\n",
       "      <td id=\"T_1c241_row4_col14\" class=\"data row4 col14\" >6.21%</td>\n",
       "      <td id=\"T_1c241_row4_col15\" class=\"data row4 col15\" >5.89%</td>\n",
       "      <td id=\"T_1c241_row4_col16\" class=\"data row4 col16\" >5.76%</td>\n",
       "      <td id=\"T_1c241_row4_col17\" class=\"data row4 col17\" >4.64%</td>\n",
       "      <td id=\"T_1c241_row4_col18\" class=\"data row4 col18\" >5.03%</td>\n",
       "      <td id=\"T_1c241_row4_col19\" class=\"data row4 col19\" >5.48%</td>\n",
       "      <td id=\"T_1c241_row4_col20\" class=\"data row4 col20\" >5.39%</td>\n",
       "      <td id=\"T_1c241_row4_col21\" class=\"data row4 col21\" >6.12%</td>\n",
       "      <td id=\"T_1c241_row4_col22\" class=\"data row4 col22\" >5.82%</td>\n",
       "      <td id=\"T_1c241_row4_col23\" class=\"data row4 col23\" >5.02%</td>\n",
       "      <td id=\"T_1c241_row4_col24\" class=\"data row4 col24\" >5.35%</td>\n",
       "      <td id=\"T_1c241_row4_col25\" class=\"data row4 col25\" >5.75%</td>\n",
       "      <td id=\"T_1c241_row4_col26\" class=\"data row4 col26\" >5.57%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_1c241_row5_col0\" class=\"data row5 col0\" >6.28%</td>\n",
       "      <td id=\"T_1c241_row5_col1\" class=\"data row5 col1\" >7.64%</td>\n",
       "      <td id=\"T_1c241_row5_col2\" class=\"data row5 col2\" >5.83%</td>\n",
       "      <td id=\"T_1c241_row5_col3\" class=\"data row5 col3\" >5.97%</td>\n",
       "      <td id=\"T_1c241_row5_col4\" class=\"data row5 col4\" >6.42%</td>\n",
       "      <td id=\"T_1c241_row5_col5\" class=\"data row5 col5\" >5.84%</td>\n",
       "      <td id=\"T_1c241_row5_col6\" class=\"data row5 col6\" >6.46%</td>\n",
       "      <td id=\"T_1c241_row5_col7\" class=\"data row5 col7\" >5.78%</td>\n",
       "      <td id=\"T_1c241_row5_col8\" class=\"data row5 col8\" >6.82%</td>\n",
       "      <td id=\"T_1c241_row5_col9\" class=\"data row5 col9\" >7.08%</td>\n",
       "      <td id=\"T_1c241_row5_col10\" class=\"data row5 col10\" >8.41%</td>\n",
       "      <td id=\"T_1c241_row5_col11\" class=\"data row5 col11\" >9.11%</td>\n",
       "      <td id=\"T_1c241_row5_col12\" class=\"data row5 col12\" >8.84%</td>\n",
       "      <td id=\"T_1c241_row5_col13\" class=\"data row5 col13\" >6.57%</td>\n",
       "      <td id=\"T_1c241_row5_col14\" class=\"data row5 col14\" >6.77%</td>\n",
       "      <td id=\"T_1c241_row5_col15\" class=\"data row5 col15\" >9.08%</td>\n",
       "      <td id=\"T_1c241_row5_col16\" class=\"data row5 col16\" >8.35%</td>\n",
       "      <td id=\"T_1c241_row5_col17\" class=\"data row5 col17\" >7.71%</td>\n",
       "      <td id=\"T_1c241_row5_col18\" class=\"data row5 col18\" >7.77%</td>\n",
       "      <td id=\"T_1c241_row5_col19\" class=\"data row5 col19\" >8.19%</td>\n",
       "      <td id=\"T_1c241_row5_col20\" class=\"data row5 col20\" >8.40%</td>\n",
       "      <td id=\"T_1c241_row5_col21\" class=\"data row5 col21\" >8.72%</td>\n",
       "      <td id=\"T_1c241_row5_col22\" class=\"data row5 col22\" >8.38%</td>\n",
       "      <td id=\"T_1c241_row5_col23\" class=\"data row5 col23\" >7.63%</td>\n",
       "      <td id=\"T_1c241_row5_col24\" class=\"data row5 col24\" >7.63%</td>\n",
       "      <td id=\"T_1c241_row5_col25\" class=\"data row5 col25\" >7.96%</td>\n",
       "      <td id=\"T_1c241_row5_col26\" class=\"data row5 col26\" >8.43%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_1c241_row6_col0\" class=\"data row6 col0\" >4.49%</td>\n",
       "      <td id=\"T_1c241_row6_col1\" class=\"data row6 col1\" >3.90%</td>\n",
       "      <td id=\"T_1c241_row6_col2\" class=\"data row6 col2\" >4.70%</td>\n",
       "      <td id=\"T_1c241_row6_col3\" class=\"data row6 col3\" >4.67%</td>\n",
       "      <td id=\"T_1c241_row6_col4\" class=\"data row6 col4\" >4.61%</td>\n",
       "      <td id=\"T_1c241_row6_col5\" class=\"data row6 col5\" >4.47%</td>\n",
       "      <td id=\"T_1c241_row6_col6\" class=\"data row6 col6\" >4.50%</td>\n",
       "      <td id=\"T_1c241_row6_col7\" class=\"data row6 col7\" >4.94%</td>\n",
       "      <td id=\"T_1c241_row6_col8\" class=\"data row6 col8\" >4.73%</td>\n",
       "      <td id=\"T_1c241_row6_col9\" class=\"data row6 col9\" >4.51%</td>\n",
       "      <td id=\"T_1c241_row6_col10\" class=\"data row6 col10\" >4.06%</td>\n",
       "      <td id=\"T_1c241_row6_col11\" class=\"data row6 col11\" >3.67%</td>\n",
       "      <td id=\"T_1c241_row6_col12\" class=\"data row6 col12\" >3.75%</td>\n",
       "      <td id=\"T_1c241_row6_col13\" class=\"data row6 col13\" >4.55%</td>\n",
       "      <td id=\"T_1c241_row6_col14\" class=\"data row6 col14\" >4.37%</td>\n",
       "      <td id=\"T_1c241_row6_col15\" class=\"data row6 col15\" >3.17%</td>\n",
       "      <td id=\"T_1c241_row6_col16\" class=\"data row6 col16\" >1.53%</td>\n",
       "      <td id=\"T_1c241_row6_col17\" class=\"data row6 col17\" >1.97%</td>\n",
       "      <td id=\"T_1c241_row6_col18\" class=\"data row6 col18\" >2.33%</td>\n",
       "      <td id=\"T_1c241_row6_col19\" class=\"data row6 col19\" >2.64%</td>\n",
       "      <td id=\"T_1c241_row6_col20\" class=\"data row6 col20\" >1.80%</td>\n",
       "      <td id=\"T_1c241_row6_col21\" class=\"data row6 col21\" >3.55%</td>\n",
       "      <td id=\"T_1c241_row6_col22\" class=\"data row6 col22\" >1.64%</td>\n",
       "      <td id=\"T_1c241_row6_col23\" class=\"data row6 col23\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row6_col24\" class=\"data row6 col24\" >2.62%</td>\n",
       "      <td id=\"T_1c241_row6_col25\" class=\"data row6 col25\" >2.96%</td>\n",
       "      <td id=\"T_1c241_row6_col26\" class=\"data row6 col26\" >1.92%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_1c241_row7_col0\" class=\"data row7 col0\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row7_col1\" class=\"data row7 col1\" >1.73%</td>\n",
       "      <td id=\"T_1c241_row7_col2\" class=\"data row7 col2\" >2.24%</td>\n",
       "      <td id=\"T_1c241_row7_col3\" class=\"data row7 col3\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row7_col4\" class=\"data row7 col4\" >2.15%</td>\n",
       "      <td id=\"T_1c241_row7_col5\" class=\"data row7 col5\" >2.30%</td>\n",
       "      <td id=\"T_1c241_row7_col6\" class=\"data row7 col6\" >2.17%</td>\n",
       "      <td id=\"T_1c241_row7_col7\" class=\"data row7 col7\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row7_col8\" class=\"data row7 col8\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row7_col9\" class=\"data row7 col9\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row7_col10\" class=\"data row7 col10\" >2.23%</td>\n",
       "      <td id=\"T_1c241_row7_col11\" class=\"data row7 col11\" >2.20%</td>\n",
       "      <td id=\"T_1c241_row7_col12\" class=\"data row7 col12\" >1.64%</td>\n",
       "      <td id=\"T_1c241_row7_col13\" class=\"data row7 col13\" >2.07%</td>\n",
       "      <td id=\"T_1c241_row7_col14\" class=\"data row7 col14\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row7_col15\" class=\"data row7 col15\" >2.70%</td>\n",
       "      <td id=\"T_1c241_row7_col16\" class=\"data row7 col16\" >3.10%</td>\n",
       "      <td id=\"T_1c241_row7_col17\" class=\"data row7 col17\" >2.98%</td>\n",
       "      <td id=\"T_1c241_row7_col18\" class=\"data row7 col18\" >2.69%</td>\n",
       "      <td id=\"T_1c241_row7_col19\" class=\"data row7 col19\" >2.72%</td>\n",
       "      <td id=\"T_1c241_row7_col20\" class=\"data row7 col20\" >3.00%</td>\n",
       "      <td id=\"T_1c241_row7_col21\" class=\"data row7 col21\" >2.46%</td>\n",
       "      <td id=\"T_1c241_row7_col22\" class=\"data row7 col22\" >2.92%</td>\n",
       "      <td id=\"T_1c241_row7_col23\" class=\"data row7 col23\" >2.76%</td>\n",
       "      <td id=\"T_1c241_row7_col24\" class=\"data row7 col24\" >2.56%</td>\n",
       "      <td id=\"T_1c241_row7_col25\" class=\"data row7 col25\" >2.58%</td>\n",
       "      <td id=\"T_1c241_row7_col26\" class=\"data row7 col26\" >2.83%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_1c241_row8_col0\" class=\"data row8 col0\" >3.10%</td>\n",
       "      <td id=\"T_1c241_row8_col1\" class=\"data row8 col1\" >2.25%</td>\n",
       "      <td id=\"T_1c241_row8_col2\" class=\"data row8 col2\" >3.29%</td>\n",
       "      <td id=\"T_1c241_row8_col3\" class=\"data row8 col3\" >3.20%</td>\n",
       "      <td id=\"T_1c241_row8_col4\" class=\"data row8 col4\" >3.01%</td>\n",
       "      <td id=\"T_1c241_row8_col5\" class=\"data row8 col5\" >3.33%</td>\n",
       "      <td id=\"T_1c241_row8_col6\" class=\"data row8 col6\" >3.00%</td>\n",
       "      <td id=\"T_1c241_row8_col7\" class=\"data row8 col7\" >2.95%</td>\n",
       "      <td id=\"T_1c241_row8_col8\" class=\"data row8 col8\" >2.87%</td>\n",
       "      <td id=\"T_1c241_row8_col9\" class=\"data row8 col9\" >2.86%</td>\n",
       "      <td id=\"T_1c241_row8_col10\" class=\"data row8 col10\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row8_col11\" class=\"data row8 col11\" >1.95%</td>\n",
       "      <td id=\"T_1c241_row8_col12\" class=\"data row8 col12\" >2.31%</td>\n",
       "      <td id=\"T_1c241_row8_col13\" class=\"data row8 col13\" >2.98%</td>\n",
       "      <td id=\"T_1c241_row8_col14\" class=\"data row8 col14\" >2.98%</td>\n",
       "      <td id=\"T_1c241_row8_col15\" class=\"data row8 col15\" >2.39%</td>\n",
       "      <td id=\"T_1c241_row8_col16\" class=\"data row8 col16\" >2.88%</td>\n",
       "      <td id=\"T_1c241_row8_col17\" class=\"data row8 col17\" >2.63%</td>\n",
       "      <td id=\"T_1c241_row8_col18\" class=\"data row8 col18\" >2.61%</td>\n",
       "      <td id=\"T_1c241_row8_col19\" class=\"data row8 col19\" >2.48%</td>\n",
       "      <td id=\"T_1c241_row8_col20\" class=\"data row8 col20\" >2.71%</td>\n",
       "      <td id=\"T_1c241_row8_col21\" class=\"data row8 col21\" >2.42%</td>\n",
       "      <td id=\"T_1c241_row8_col22\" class=\"data row8 col22\" >2.89%</td>\n",
       "      <td id=\"T_1c241_row8_col23\" class=\"data row8 col23\" >2.63%</td>\n",
       "      <td id=\"T_1c241_row8_col24\" class=\"data row8 col24\" >2.58%</td>\n",
       "      <td id=\"T_1c241_row8_col25\" class=\"data row8 col25\" >2.47%</td>\n",
       "      <td id=\"T_1c241_row8_col26\" class=\"data row8 col26\" >2.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_1c241_row9_col0\" class=\"data row9 col0\" >2.41%</td>\n",
       "      <td id=\"T_1c241_row9_col1\" class=\"data row9 col1\" >2.25%</td>\n",
       "      <td id=\"T_1c241_row9_col2\" class=\"data row9 col2\" >2.42%</td>\n",
       "      <td id=\"T_1c241_row9_col3\" class=\"data row9 col3\" >2.43%</td>\n",
       "      <td id=\"T_1c241_row9_col4\" class=\"data row9 col4\" >2.42%</td>\n",
       "      <td id=\"T_1c241_row9_col5\" class=\"data row9 col5\" >2.39%</td>\n",
       "      <td id=\"T_1c241_row9_col6\" class=\"data row9 col6\" >2.41%</td>\n",
       "      <td id=\"T_1c241_row9_col7\" class=\"data row9 col7\" >2.24%</td>\n",
       "      <td id=\"T_1c241_row9_col8\" class=\"data row9 col8\" >2.37%</td>\n",
       "      <td id=\"T_1c241_row9_col9\" class=\"data row9 col9\" >2.40%</td>\n",
       "      <td id=\"T_1c241_row9_col10\" class=\"data row9 col10\" >2.43%</td>\n",
       "      <td id=\"T_1c241_row9_col11\" class=\"data row9 col11\" >2.29%</td>\n",
       "      <td id=\"T_1c241_row9_col12\" class=\"data row9 col12\" >1.83%</td>\n",
       "      <td id=\"T_1c241_row9_col13\" class=\"data row9 col13\" >2.42%</td>\n",
       "      <td id=\"T_1c241_row9_col14\" class=\"data row9 col14\" >2.41%</td>\n",
       "      <td id=\"T_1c241_row9_col15\" class=\"data row9 col15\" >1.68%</td>\n",
       "      <td id=\"T_1c241_row9_col16\" class=\"data row9 col16\" >1.79%</td>\n",
       "      <td id=\"T_1c241_row9_col17\" class=\"data row9 col17\" >2.16%</td>\n",
       "      <td id=\"T_1c241_row9_col18\" class=\"data row9 col18\" >1.96%</td>\n",
       "      <td id=\"T_1c241_row9_col19\" class=\"data row9 col19\" >1.87%</td>\n",
       "      <td id=\"T_1c241_row9_col20\" class=\"data row9 col20\" >1.94%</td>\n",
       "      <td id=\"T_1c241_row9_col21\" class=\"data row9 col21\" >1.65%</td>\n",
       "      <td id=\"T_1c241_row9_col22\" class=\"data row9 col22\" >1.65%</td>\n",
       "      <td id=\"T_1c241_row9_col23\" class=\"data row9 col23\" >1.99%</td>\n",
       "      <td id=\"T_1c241_row9_col24\" class=\"data row9 col24\" >1.83%</td>\n",
       "      <td id=\"T_1c241_row9_col25\" class=\"data row9 col25\" >1.78%</td>\n",
       "      <td id=\"T_1c241_row9_col26\" class=\"data row9 col26\" >1.78%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_1c241_row10_col0\" class=\"data row10 col0\" >2.67%</td>\n",
       "      <td id=\"T_1c241_row10_col1\" class=\"data row10 col1\" >2.75%</td>\n",
       "      <td id=\"T_1c241_row10_col2\" class=\"data row10 col2\" >2.73%</td>\n",
       "      <td id=\"T_1c241_row10_col3\" class=\"data row10 col3\" >2.69%</td>\n",
       "      <td id=\"T_1c241_row10_col4\" class=\"data row10 col4\" >2.72%</td>\n",
       "      <td id=\"T_1c241_row10_col5\" class=\"data row10 col5\" >2.86%</td>\n",
       "      <td id=\"T_1c241_row10_col6\" class=\"data row10 col6\" >2.77%</td>\n",
       "      <td id=\"T_1c241_row10_col7\" class=\"data row10 col7\" >2.61%</td>\n",
       "      <td id=\"T_1c241_row10_col8\" class=\"data row10 col8\" >2.63%</td>\n",
       "      <td id=\"T_1c241_row10_col9\" class=\"data row10 col9\" >2.64%</td>\n",
       "      <td id=\"T_1c241_row10_col10\" class=\"data row10 col10\" >2.64%</td>\n",
       "      <td id=\"T_1c241_row10_col11\" class=\"data row10 col11\" >2.42%</td>\n",
       "      <td id=\"T_1c241_row10_col12\" class=\"data row10 col12\" >2.27%</td>\n",
       "      <td id=\"T_1c241_row10_col13\" class=\"data row10 col13\" >2.56%</td>\n",
       "      <td id=\"T_1c241_row10_col14\" class=\"data row10 col14\" >2.58%</td>\n",
       "      <td id=\"T_1c241_row10_col15\" class=\"data row10 col15\" >2.54%</td>\n",
       "      <td id=\"T_1c241_row10_col16\" class=\"data row10 col16\" >3.79%</td>\n",
       "      <td id=\"T_1c241_row10_col17\" class=\"data row10 col17\" >4.16%</td>\n",
       "      <td id=\"T_1c241_row10_col18\" class=\"data row10 col18\" >3.42%</td>\n",
       "      <td id=\"T_1c241_row10_col19\" class=\"data row10 col19\" >3.08%</td>\n",
       "      <td id=\"T_1c241_row10_col20\" class=\"data row10 col20\" >3.79%</td>\n",
       "      <td id=\"T_1c241_row10_col21\" class=\"data row10 col21\" >2.58%</td>\n",
       "      <td id=\"T_1c241_row10_col22\" class=\"data row10 col22\" >3.81%</td>\n",
       "      <td id=\"T_1c241_row10_col23\" class=\"data row10 col23\" >3.99%</td>\n",
       "      <td id=\"T_1c241_row10_col24\" class=\"data row10 col24\" >3.37%</td>\n",
       "      <td id=\"T_1c241_row10_col25\" class=\"data row10 col25\" >3.09%</td>\n",
       "      <td id=\"T_1c241_row10_col26\" class=\"data row10 col26\" >3.77%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_1c241_row11_col0\" class=\"data row11 col0\" >2.07%</td>\n",
       "      <td id=\"T_1c241_row11_col1\" class=\"data row11 col1\" >1.66%</td>\n",
       "      <td id=\"T_1c241_row11_col2\" class=\"data row11 col2\" >2.13%</td>\n",
       "      <td id=\"T_1c241_row11_col3\" class=\"data row11 col3\" >2.10%</td>\n",
       "      <td id=\"T_1c241_row11_col4\" class=\"data row11 col4\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row11_col5\" class=\"data row11 col5\" >2.07%</td>\n",
       "      <td id=\"T_1c241_row11_col6\" class=\"data row11 col6\" >2.00%</td>\n",
       "      <td id=\"T_1c241_row11_col7\" class=\"data row11 col7\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row11_col8\" class=\"data row11 col8\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row11_col9\" class=\"data row11 col9\" >1.92%</td>\n",
       "      <td id=\"T_1c241_row11_col10\" class=\"data row11 col10\" >1.68%</td>\n",
       "      <td id=\"T_1c241_row11_col11\" class=\"data row11 col11\" >1.50%</td>\n",
       "      <td id=\"T_1c241_row11_col12\" class=\"data row11 col12\" >1.72%</td>\n",
       "      <td id=\"T_1c241_row11_col13\" class=\"data row11 col13\" >2.01%</td>\n",
       "      <td id=\"T_1c241_row11_col14\" class=\"data row11 col14\" >2.01%</td>\n",
       "      <td id=\"T_1c241_row11_col15\" class=\"data row11 col15\" >1.72%</td>\n",
       "      <td id=\"T_1c241_row11_col16\" class=\"data row11 col16\" >1.37%</td>\n",
       "      <td id=\"T_1c241_row11_col17\" class=\"data row11 col17\" >2.06%</td>\n",
       "      <td id=\"T_1c241_row11_col18\" class=\"data row11 col18\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row11_col19\" class=\"data row11 col19\" >1.87%</td>\n",
       "      <td id=\"T_1c241_row11_col20\" class=\"data row11 col20\" >1.59%</td>\n",
       "      <td id=\"T_1c241_row11_col21\" class=\"data row11 col21\" >1.74%</td>\n",
       "      <td id=\"T_1c241_row11_col22\" class=\"data row11 col22\" >1.31%</td>\n",
       "      <td id=\"T_1c241_row11_col23\" class=\"data row11 col23\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row11_col24\" class=\"data row11 col24\" >1.90%</td>\n",
       "      <td id=\"T_1c241_row11_col25\" class=\"data row11 col25\" >1.85%</td>\n",
       "      <td id=\"T_1c241_row11_col26\" class=\"data row11 col26\" >1.52%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_1c241_row12_col0\" class=\"data row12 col0\" >5.56%</td>\n",
       "      <td id=\"T_1c241_row12_col1\" class=\"data row12 col1\" >7.24%</td>\n",
       "      <td id=\"T_1c241_row12_col2\" class=\"data row12 col2\" >5.59%</td>\n",
       "      <td id=\"T_1c241_row12_col3\" class=\"data row12 col3\" >5.54%</td>\n",
       "      <td id=\"T_1c241_row12_col4\" class=\"data row12 col4\" >5.68%</td>\n",
       "      <td id=\"T_1c241_row12_col5\" class=\"data row12 col5\" >5.91%</td>\n",
       "      <td id=\"T_1c241_row12_col6\" class=\"data row12 col6\" >5.85%</td>\n",
       "      <td id=\"T_1c241_row12_col7\" class=\"data row12 col7\" >5.79%</td>\n",
       "      <td id=\"T_1c241_row12_col8\" class=\"data row12 col8\" >5.56%</td>\n",
       "      <td id=\"T_1c241_row12_col9\" class=\"data row12 col9\" >5.60%</td>\n",
       "      <td id=\"T_1c241_row12_col10\" class=\"data row12 col10\" >6.88%</td>\n",
       "      <td id=\"T_1c241_row12_col11\" class=\"data row12 col11\" >7.56%</td>\n",
       "      <td id=\"T_1c241_row12_col12\" class=\"data row12 col12\" >5.79%</td>\n",
       "      <td id=\"T_1c241_row12_col13\" class=\"data row12 col13\" >5.35%</td>\n",
       "      <td id=\"T_1c241_row12_col14\" class=\"data row12 col14\" >5.35%</td>\n",
       "      <td id=\"T_1c241_row12_col15\" class=\"data row12 col15\" >5.92%</td>\n",
       "      <td id=\"T_1c241_row12_col16\" class=\"data row12 col16\" >11.07%</td>\n",
       "      <td id=\"T_1c241_row12_col17\" class=\"data row12 col17\" >10.84%</td>\n",
       "      <td id=\"T_1c241_row12_col18\" class=\"data row12 col18\" >9.14%</td>\n",
       "      <td id=\"T_1c241_row12_col19\" class=\"data row12 col19\" >7.45%</td>\n",
       "      <td id=\"T_1c241_row12_col20\" class=\"data row12 col20\" >10.55%</td>\n",
       "      <td id=\"T_1c241_row12_col21\" class=\"data row12 col21\" >5.93%</td>\n",
       "      <td id=\"T_1c241_row12_col22\" class=\"data row12 col22\" >11.28%</td>\n",
       "      <td id=\"T_1c241_row12_col23\" class=\"data row12 col23\" >10.66%</td>\n",
       "      <td id=\"T_1c241_row12_col24\" class=\"data row12 col24\" >9.02%</td>\n",
       "      <td id=\"T_1c241_row12_col25\" class=\"data row12 col25\" >7.48%</td>\n",
       "      <td id=\"T_1c241_row12_col26\" class=\"data row12 col26\" >10.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_1c241_row13_col0\" class=\"data row13 col0\" >5.46%</td>\n",
       "      <td id=\"T_1c241_row13_col1\" class=\"data row13 col1\" >5.77%</td>\n",
       "      <td id=\"T_1c241_row13_col2\" class=\"data row13 col2\" >5.36%</td>\n",
       "      <td id=\"T_1c241_row13_col3\" class=\"data row13 col3\" >5.38%</td>\n",
       "      <td id=\"T_1c241_row13_col4\" class=\"data row13 col4\" >5.37%</td>\n",
       "      <td id=\"T_1c241_row13_col5\" class=\"data row13 col5\" >5.08%</td>\n",
       "      <td id=\"T_1c241_row13_col6\" class=\"data row13 col6\" >5.24%</td>\n",
       "      <td id=\"T_1c241_row13_col7\" class=\"data row13 col7\" >5.26%</td>\n",
       "      <td id=\"T_1c241_row13_col8\" class=\"data row13 col8\" >5.39%</td>\n",
       "      <td id=\"T_1c241_row13_col9\" class=\"data row13 col9\" >5.41%</td>\n",
       "      <td id=\"T_1c241_row13_col10\" class=\"data row13 col10\" >5.22%</td>\n",
       "      <td id=\"T_1c241_row13_col11\" class=\"data row13 col11\" >4.78%</td>\n",
       "      <td id=\"T_1c241_row13_col12\" class=\"data row13 col12\" >5.20%</td>\n",
       "      <td id=\"T_1c241_row13_col13\" class=\"data row13 col13\" >5.58%</td>\n",
       "      <td id=\"T_1c241_row13_col14\" class=\"data row13 col14\" >5.68%</td>\n",
       "      <td id=\"T_1c241_row13_col15\" class=\"data row13 col15\" >4.01%</td>\n",
       "      <td id=\"T_1c241_row13_col16\" class=\"data row13 col16\" >2.41%</td>\n",
       "      <td id=\"T_1c241_row13_col17\" class=\"data row13 col17\" >2.65%</td>\n",
       "      <td id=\"T_1c241_row13_col18\" class=\"data row13 col18\" >3.00%</td>\n",
       "      <td id=\"T_1c241_row13_col19\" class=\"data row13 col19\" >3.38%</td>\n",
       "      <td id=\"T_1c241_row13_col20\" class=\"data row13 col20\" >2.61%</td>\n",
       "      <td id=\"T_1c241_row13_col21\" class=\"data row13 col21\" >4.14%</td>\n",
       "      <td id=\"T_1c241_row13_col22\" class=\"data row13 col22\" >2.55%</td>\n",
       "      <td id=\"T_1c241_row13_col23\" class=\"data row13 col23\" >2.76%</td>\n",
       "      <td id=\"T_1c241_row13_col24\" class=\"data row13 col24\" >3.16%</td>\n",
       "      <td id=\"T_1c241_row13_col25\" class=\"data row13 col25\" >3.52%</td>\n",
       "      <td id=\"T_1c241_row13_col26\" class=\"data row13 col26\" >2.72%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_1c241_row14_col0\" class=\"data row14 col0\" >3.97%</td>\n",
       "      <td id=\"T_1c241_row14_col1\" class=\"data row14 col1\" >3.70%</td>\n",
       "      <td id=\"T_1c241_row14_col2\" class=\"data row14 col2\" >4.08%</td>\n",
       "      <td id=\"T_1c241_row14_col3\" class=\"data row14 col3\" >3.99%</td>\n",
       "      <td id=\"T_1c241_row14_col4\" class=\"data row14 col4\" >4.10%</td>\n",
       "      <td id=\"T_1c241_row14_col5\" class=\"data row14 col5\" >4.38%</td>\n",
       "      <td id=\"T_1c241_row14_col6\" class=\"data row14 col6\" >4.24%</td>\n",
       "      <td id=\"T_1c241_row14_col7\" class=\"data row14 col7\" >3.99%</td>\n",
       "      <td id=\"T_1c241_row14_col8\" class=\"data row14 col8\" >3.94%</td>\n",
       "      <td id=\"T_1c241_row14_col9\" class=\"data row14 col9\" >4.06%</td>\n",
       "      <td id=\"T_1c241_row14_col10\" class=\"data row14 col10\" >4.69%</td>\n",
       "      <td id=\"T_1c241_row14_col11\" class=\"data row14 col11\" >4.70%</td>\n",
       "      <td id=\"T_1c241_row14_col12\" class=\"data row14 col12\" >4.06%</td>\n",
       "      <td id=\"T_1c241_row14_col13\" class=\"data row14 col13\" >3.78%</td>\n",
       "      <td id=\"T_1c241_row14_col14\" class=\"data row14 col14\" >3.79%</td>\n",
       "      <td id=\"T_1c241_row14_col15\" class=\"data row14 col15\" >5.24%</td>\n",
       "      <td id=\"T_1c241_row14_col16\" class=\"data row14 col16\" >10.41%</td>\n",
       "      <td id=\"T_1c241_row14_col17\" class=\"data row14 col17\" >7.49%</td>\n",
       "      <td id=\"T_1c241_row14_col18\" class=\"data row14 col18\" >7.38%</td>\n",
       "      <td id=\"T_1c241_row14_col19\" class=\"data row14 col19\" >6.57%</td>\n",
       "      <td id=\"T_1c241_row14_col20\" class=\"data row14 col20\" >9.04%</td>\n",
       "      <td id=\"T_1c241_row14_col21\" class=\"data row14 col21\" >4.96%</td>\n",
       "      <td id=\"T_1c241_row14_col22\" class=\"data row14 col22\" >10.12%</td>\n",
       "      <td id=\"T_1c241_row14_col23\" class=\"data row14 col23\" >7.30%</td>\n",
       "      <td id=\"T_1c241_row14_col24\" class=\"data row14 col24\" >7.00%</td>\n",
       "      <td id=\"T_1c241_row14_col25\" class=\"data row14 col25\" >6.22%</td>\n",
       "      <td id=\"T_1c241_row14_col26\" class=\"data row14 col26\" >8.73%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_1c241_row15_col0\" class=\"data row15 col0\" >6.17%</td>\n",
       "      <td id=\"T_1c241_row15_col1\" class=\"data row15 col1\" >7.37%</td>\n",
       "      <td id=\"T_1c241_row15_col2\" class=\"data row15 col2\" >5.85%</td>\n",
       "      <td id=\"T_1c241_row15_col3\" class=\"data row15 col3\" >6.03%</td>\n",
       "      <td id=\"T_1c241_row15_col4\" class=\"data row15 col4\" >6.09%</td>\n",
       "      <td id=\"T_1c241_row15_col5\" class=\"data row15 col5\" >5.80%</td>\n",
       "      <td id=\"T_1c241_row15_col6\" class=\"data row15 col6\" >6.07%</td>\n",
       "      <td id=\"T_1c241_row15_col7\" class=\"data row15 col7\" >6.06%</td>\n",
       "      <td id=\"T_1c241_row15_col8\" class=\"data row15 col8\" >6.73%</td>\n",
       "      <td id=\"T_1c241_row15_col9\" class=\"data row15 col9\" >6.72%</td>\n",
       "      <td id=\"T_1c241_row15_col10\" class=\"data row15 col10\" >4.50%</td>\n",
       "      <td id=\"T_1c241_row15_col11\" class=\"data row15 col11\" >3.88%</td>\n",
       "      <td id=\"T_1c241_row15_col12\" class=\"data row15 col12\" >5.26%</td>\n",
       "      <td id=\"T_1c241_row15_col13\" class=\"data row15 col13\" >6.67%</td>\n",
       "      <td id=\"T_1c241_row15_col14\" class=\"data row15 col14\" >6.73%</td>\n",
       "      <td id=\"T_1c241_row15_col15\" class=\"data row15 col15\" >9.47%</td>\n",
       "      <td id=\"T_1c241_row15_col16\" class=\"data row15 col16\" >6.06%</td>\n",
       "      <td id=\"T_1c241_row15_col17\" class=\"data row15 col17\" >5.88%</td>\n",
       "      <td id=\"T_1c241_row15_col18\" class=\"data row15 col18\" >7.08%</td>\n",
       "      <td id=\"T_1c241_row15_col19\" class=\"data row15 col19\" >8.04%</td>\n",
       "      <td id=\"T_1c241_row15_col20\" class=\"data row15 col20\" >6.25%</td>\n",
       "      <td id=\"T_1c241_row15_col21\" class=\"data row15 col21\" >9.15%</td>\n",
       "      <td id=\"T_1c241_row15_col22\" class=\"data row15 col22\" >6.28%</td>\n",
       "      <td id=\"T_1c241_row15_col23\" class=\"data row15 col23\" >6.00%</td>\n",
       "      <td id=\"T_1c241_row15_col24\" class=\"data row15 col24\" >7.08%</td>\n",
       "      <td id=\"T_1c241_row15_col25\" class=\"data row15 col25\" >7.89%</td>\n",
       "      <td id=\"T_1c241_row15_col26\" class=\"data row15 col26\" >6.44%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_1c241_row16_col0\" class=\"data row16 col0\" >2.34%</td>\n",
       "      <td id=\"T_1c241_row16_col1\" class=\"data row16 col1\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row16_col2\" class=\"data row16 col2\" >2.31%</td>\n",
       "      <td id=\"T_1c241_row16_col3\" class=\"data row16 col3\" >2.31%</td>\n",
       "      <td id=\"T_1c241_row16_col4\" class=\"data row16 col4\" >2.32%</td>\n",
       "      <td id=\"T_1c241_row16_col5\" class=\"data row16 col5\" >2.34%</td>\n",
       "      <td id=\"T_1c241_row16_col6\" class=\"data row16 col6\" >2.33%</td>\n",
       "      <td id=\"T_1c241_row16_col7\" class=\"data row16 col7\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row16_col8\" class=\"data row16 col8\" >2.28%</td>\n",
       "      <td id=\"T_1c241_row16_col9\" class=\"data row16 col9\" >2.29%</td>\n",
       "      <td id=\"T_1c241_row16_col10\" class=\"data row16 col10\" >2.29%</td>\n",
       "      <td id=\"T_1c241_row16_col11\" class=\"data row16 col11\" >2.17%</td>\n",
       "      <td id=\"T_1c241_row16_col12\" class=\"data row16 col12\" >2.56%</td>\n",
       "      <td id=\"T_1c241_row16_col13\" class=\"data row16 col13\" >2.32%</td>\n",
       "      <td id=\"T_1c241_row16_col14\" class=\"data row16 col14\" >2.35%</td>\n",
       "      <td id=\"T_1c241_row16_col15\" class=\"data row16 col15\" >1.86%</td>\n",
       "      <td id=\"T_1c241_row16_col16\" class=\"data row16 col16\" >2.20%</td>\n",
       "      <td id=\"T_1c241_row16_col17\" class=\"data row16 col17\" >2.25%</td>\n",
       "      <td id=\"T_1c241_row16_col18\" class=\"data row16 col18\" >1.99%</td>\n",
       "      <td id=\"T_1c241_row16_col19\" class=\"data row16 col19\" >1.96%</td>\n",
       "      <td id=\"T_1c241_row16_col20\" class=\"data row16 col20\" >2.20%</td>\n",
       "      <td id=\"T_1c241_row16_col21\" class=\"data row16 col21\" >1.90%</td>\n",
       "      <td id=\"T_1c241_row16_col22\" class=\"data row16 col22\" >2.10%</td>\n",
       "      <td id=\"T_1c241_row16_col23\" class=\"data row16 col23\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row16_col24\" class=\"data row16 col24\" >1.98%</td>\n",
       "      <td id=\"T_1c241_row16_col25\" class=\"data row16 col25\" >1.97%</td>\n",
       "      <td id=\"T_1c241_row16_col26\" class=\"data row16 col26\" >2.16%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_1c241_row17_col0\" class=\"data row17 col0\" >5.99%</td>\n",
       "      <td id=\"T_1c241_row17_col1\" class=\"data row17 col1\" >6.94%</td>\n",
       "      <td id=\"T_1c241_row17_col2\" class=\"data row17 col2\" >5.58%</td>\n",
       "      <td id=\"T_1c241_row17_col3\" class=\"data row17 col3\" >5.69%</td>\n",
       "      <td id=\"T_1c241_row17_col4\" class=\"data row17 col4\" >6.06%</td>\n",
       "      <td id=\"T_1c241_row17_col5\" class=\"data row17 col5\" >5.25%</td>\n",
       "      <td id=\"T_1c241_row17_col6\" class=\"data row17 col6\" >5.90%</td>\n",
       "      <td id=\"T_1c241_row17_col7\" class=\"data row17 col7\" >5.86%</td>\n",
       "      <td id=\"T_1c241_row17_col8\" class=\"data row17 col8\" >6.21%</td>\n",
       "      <td id=\"T_1c241_row17_col9\" class=\"data row17 col9\" >6.40%</td>\n",
       "      <td id=\"T_1c241_row17_col10\" class=\"data row17 col10\" >7.54%</td>\n",
       "      <td id=\"T_1c241_row17_col11\" class=\"data row17 col11\" >8.10%</td>\n",
       "      <td id=\"T_1c241_row17_col12\" class=\"data row17 col12\" >9.02%</td>\n",
       "      <td id=\"T_1c241_row17_col13\" class=\"data row17 col13\" >6.18%</td>\n",
       "      <td id=\"T_1c241_row17_col14\" class=\"data row17 col14\" >6.45%</td>\n",
       "      <td id=\"T_1c241_row17_col15\" class=\"data row17 col15\" >5.79%</td>\n",
       "      <td id=\"T_1c241_row17_col16\" class=\"data row17 col16\" >2.60%</td>\n",
       "      <td id=\"T_1c241_row17_col17\" class=\"data row17 col17\" >3.86%</td>\n",
       "      <td id=\"T_1c241_row17_col18\" class=\"data row17 col18\" >4.66%</td>\n",
       "      <td id=\"T_1c241_row17_col19\" class=\"data row17 col19\" >5.19%</td>\n",
       "      <td id=\"T_1c241_row17_col20\" class=\"data row17 col20\" >3.16%</td>\n",
       "      <td id=\"T_1c241_row17_col21\" class=\"data row17 col21\" >5.68%</td>\n",
       "      <td id=\"T_1c241_row17_col22\" class=\"data row17 col22\" >2.59%</td>\n",
       "      <td id=\"T_1c241_row17_col23\" class=\"data row17 col23\" >3.88%</td>\n",
       "      <td id=\"T_1c241_row17_col24\" class=\"data row17 col24\" >4.66%</td>\n",
       "      <td id=\"T_1c241_row17_col25\" class=\"data row17 col25\" >5.11%</td>\n",
       "      <td id=\"T_1c241_row17_col26\" class=\"data row17 col26\" >3.14%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_1c241_row18_col0\" class=\"data row18 col0\" >2.28%</td>\n",
       "      <td id=\"T_1c241_row18_col1\" class=\"data row18 col1\" >2.02%</td>\n",
       "      <td id=\"T_1c241_row18_col2\" class=\"data row18 col2\" >2.38%</td>\n",
       "      <td id=\"T_1c241_row18_col3\" class=\"data row18 col3\" >2.36%</td>\n",
       "      <td id=\"T_1c241_row18_col4\" class=\"data row18 col4\" >2.20%</td>\n",
       "      <td id=\"T_1c241_row18_col5\" class=\"data row18 col5\" >2.25%</td>\n",
       "      <td id=\"T_1c241_row18_col6\" class=\"data row18 col6\" >2.14%</td>\n",
       "      <td id=\"T_1c241_row18_col7\" class=\"data row18 col7\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row18_col8\" class=\"data row18 col8\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row18_col9\" class=\"data row18 col9\" >1.98%</td>\n",
       "      <td id=\"T_1c241_row18_col10\" class=\"data row18 col10\" >1.91%</td>\n",
       "      <td id=\"T_1c241_row18_col11\" class=\"data row18 col11\" >1.90%</td>\n",
       "      <td id=\"T_1c241_row18_col12\" class=\"data row18 col12\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row18_col13\" class=\"data row18 col13\" >2.24%</td>\n",
       "      <td id=\"T_1c241_row18_col14\" class=\"data row18 col14\" >2.18%</td>\n",
       "      <td id=\"T_1c241_row18_col15\" class=\"data row18 col15\" >1.36%</td>\n",
       "      <td id=\"T_1c241_row18_col16\" class=\"data row18 col16\" >1.42%</td>\n",
       "      <td id=\"T_1c241_row18_col17\" class=\"data row18 col17\" >1.79%</td>\n",
       "      <td id=\"T_1c241_row18_col18\" class=\"data row18 col18\" >1.49%</td>\n",
       "      <td id=\"T_1c241_row18_col19\" class=\"data row18 col19\" >1.45%</td>\n",
       "      <td id=\"T_1c241_row18_col20\" class=\"data row18 col20\" >1.66%</td>\n",
       "      <td id=\"T_1c241_row18_col21\" class=\"data row18 col21\" >1.42%</td>\n",
       "      <td id=\"T_1c241_row18_col22\" class=\"data row18 col22\" >1.19%</td>\n",
       "      <td id=\"T_1c241_row18_col23\" class=\"data row18 col23\" >1.66%</td>\n",
       "      <td id=\"T_1c241_row18_col24\" class=\"data row18 col24\" >1.48%</td>\n",
       "      <td id=\"T_1c241_row18_col25\" class=\"data row18 col25\" >1.47%</td>\n",
       "      <td id=\"T_1c241_row18_col26\" class=\"data row18 col26\" >1.44%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_1c241_row19_col0\" class=\"data row19 col0\" >7.14%</td>\n",
       "      <td id=\"T_1c241_row19_col1\" class=\"data row19 col1\" >7.74%</td>\n",
       "      <td id=\"T_1c241_row19_col2\" class=\"data row19 col2\" >7.13%</td>\n",
       "      <td id=\"T_1c241_row19_col3\" class=\"data row19 col3\" >7.15%</td>\n",
       "      <td id=\"T_1c241_row19_col4\" class=\"data row19 col4\" >6.84%</td>\n",
       "      <td id=\"T_1c241_row19_col5\" class=\"data row19 col5\" >7.11%</td>\n",
       "      <td id=\"T_1c241_row19_col6\" class=\"data row19 col6\" >6.83%</td>\n",
       "      <td id=\"T_1c241_row19_col7\" class=\"data row19 col7\" >7.45%</td>\n",
       "      <td id=\"T_1c241_row19_col8\" class=\"data row19 col8\" >6.64%</td>\n",
       "      <td id=\"T_1c241_row19_col9\" class=\"data row19 col9\" >6.50%</td>\n",
       "      <td id=\"T_1c241_row19_col10\" class=\"data row19 col10\" >6.19%</td>\n",
       "      <td id=\"T_1c241_row19_col11\" class=\"data row19 col11\" >5.92%</td>\n",
       "      <td id=\"T_1c241_row19_col12\" class=\"data row19 col12\" >7.43%</td>\n",
       "      <td id=\"T_1c241_row19_col13\" class=\"data row19 col13\" >7.05%</td>\n",
       "      <td id=\"T_1c241_row19_col14\" class=\"data row19 col14\" >6.95%</td>\n",
       "      <td id=\"T_1c241_row19_col15\" class=\"data row19 col15\" >6.78%</td>\n",
       "      <td id=\"T_1c241_row19_col16\" class=\"data row19 col16\" >5.06%</td>\n",
       "      <td id=\"T_1c241_row19_col17\" class=\"data row19 col17\" >6.18%</td>\n",
       "      <td id=\"T_1c241_row19_col18\" class=\"data row19 col18\" >6.82%</td>\n",
       "      <td id=\"T_1c241_row19_col19\" class=\"data row19 col19\" >6.93%</td>\n",
       "      <td id=\"T_1c241_row19_col20\" class=\"data row19 col20\" >5.53%</td>\n",
       "      <td id=\"T_1c241_row19_col21\" class=\"data row19 col21\" >6.40%</td>\n",
       "      <td id=\"T_1c241_row19_col22\" class=\"data row19 col22\" >4.81%</td>\n",
       "      <td id=\"T_1c241_row19_col23\" class=\"data row19 col23\" >5.87%</td>\n",
       "      <td id=\"T_1c241_row19_col24\" class=\"data row19 col24\" >6.39%</td>\n",
       "      <td id=\"T_1c241_row19_col25\" class=\"data row19 col25\" >6.50%</td>\n",
       "      <td id=\"T_1c241_row19_col26\" class=\"data row19 col26\" >5.24%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_1c241_row20_col0\" class=\"data row20 col0\" >4.58%</td>\n",
       "      <td id=\"T_1c241_row20_col1\" class=\"data row20 col1\" >3.19%</td>\n",
       "      <td id=\"T_1c241_row20_col2\" class=\"data row20 col2\" >5.04%</td>\n",
       "      <td id=\"T_1c241_row20_col3\" class=\"data row20 col3\" >4.98%</td>\n",
       "      <td id=\"T_1c241_row20_col4\" class=\"data row20 col4\" >4.93%</td>\n",
       "      <td id=\"T_1c241_row20_col5\" class=\"data row20 col5\" >5.11%</td>\n",
       "      <td id=\"T_1c241_row20_col6\" class=\"data row20 col6\" >4.96%</td>\n",
       "      <td id=\"T_1c241_row20_col7\" class=\"data row20 col7\" >5.51%</td>\n",
       "      <td id=\"T_1c241_row20_col8\" class=\"data row20 col8\" >5.00%</td>\n",
       "      <td id=\"T_1c241_row20_col9\" class=\"data row20 col9\" >4.81%</td>\n",
       "      <td id=\"T_1c241_row20_col10\" class=\"data row20 col10\" >4.10%</td>\n",
       "      <td id=\"T_1c241_row20_col11\" class=\"data row20 col11\" >3.92%</td>\n",
       "      <td id=\"T_1c241_row20_col12\" class=\"data row20 col12\" >2.98%</td>\n",
       "      <td id=\"T_1c241_row20_col13\" class=\"data row20 col13\" >4.65%</td>\n",
       "      <td id=\"T_1c241_row20_col14\" class=\"data row20 col14\" >4.34%</td>\n",
       "      <td id=\"T_1c241_row20_col15\" class=\"data row20 col15\" >4.36%</td>\n",
       "      <td id=\"T_1c241_row20_col16\" class=\"data row20 col16\" >2.93%</td>\n",
       "      <td id=\"T_1c241_row20_col17\" class=\"data row20 col17\" >3.10%</td>\n",
       "      <td id=\"T_1c241_row20_col18\" class=\"data row20 col18\" >3.50%</td>\n",
       "      <td id=\"T_1c241_row20_col19\" class=\"data row20 col19\" >3.86%</td>\n",
       "      <td id=\"T_1c241_row20_col20\" class=\"data row20 col20\" >3.05%</td>\n",
       "      <td id=\"T_1c241_row20_col21\" class=\"data row20 col21\" >4.63%</td>\n",
       "      <td id=\"T_1c241_row20_col22\" class=\"data row20 col22\" >3.11%</td>\n",
       "      <td id=\"T_1c241_row20_col23\" class=\"data row20 col23\" >3.41%</td>\n",
       "      <td id=\"T_1c241_row20_col24\" class=\"data row20 col24\" >3.83%</td>\n",
       "      <td id=\"T_1c241_row20_col25\" class=\"data row20 col25\" >4.16%</td>\n",
       "      <td id=\"T_1c241_row20_col26\" class=\"data row20 col26\" >3.28%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_1c241_row21_col0\" class=\"data row21 col0\" >4.15%</td>\n",
       "      <td id=\"T_1c241_row21_col1\" class=\"data row21 col1\" >4.05%</td>\n",
       "      <td id=\"T_1c241_row21_col2\" class=\"data row21 col2\" >4.14%</td>\n",
       "      <td id=\"T_1c241_row21_col3\" class=\"data row21 col3\" >4.10%</td>\n",
       "      <td id=\"T_1c241_row21_col4\" class=\"data row21 col4\" >4.21%</td>\n",
       "      <td id=\"T_1c241_row21_col5\" class=\"data row21 col5\" >4.30%</td>\n",
       "      <td id=\"T_1c241_row21_col6\" class=\"data row21 col6\" >4.30%</td>\n",
       "      <td id=\"T_1c241_row21_col7\" class=\"data row21 col7\" >4.06%</td>\n",
       "      <td id=\"T_1c241_row21_col8\" class=\"data row21 col8\" >4.09%</td>\n",
       "      <td id=\"T_1c241_row21_col9\" class=\"data row21 col9\" >4.18%</td>\n",
       "      <td id=\"T_1c241_row21_col10\" class=\"data row21 col10\" >5.12%</td>\n",
       "      <td id=\"T_1c241_row21_col11\" class=\"data row21 col11\" >5.66%</td>\n",
       "      <td id=\"T_1c241_row21_col12\" class=\"data row21 col12\" >4.86%</td>\n",
       "      <td id=\"T_1c241_row21_col13\" class=\"data row21 col13\" >4.02%</td>\n",
       "      <td id=\"T_1c241_row21_col14\" class=\"data row21 col14\" >4.05%</td>\n",
       "      <td id=\"T_1c241_row21_col15\" class=\"data row21 col15\" >5.22%</td>\n",
       "      <td id=\"T_1c241_row21_col16\" class=\"data row21 col16\" >7.40%</td>\n",
       "      <td id=\"T_1c241_row21_col17\" class=\"data row21 col17\" >7.03%</td>\n",
       "      <td id=\"T_1c241_row21_col18\" class=\"data row21 col18\" >6.97%</td>\n",
       "      <td id=\"T_1c241_row21_col19\" class=\"data row21 col19\" >6.24%</td>\n",
       "      <td id=\"T_1c241_row21_col20\" class=\"data row21 col20\" >7.28%</td>\n",
       "      <td id=\"T_1c241_row21_col21\" class=\"data row21 col21\" >5.25%</td>\n",
       "      <td id=\"T_1c241_row21_col22\" class=\"data row21 col22\" >7.37%</td>\n",
       "      <td id=\"T_1c241_row21_col23\" class=\"data row21 col23\" >7.13%</td>\n",
       "      <td id=\"T_1c241_row21_col24\" class=\"data row21 col24\" >6.88%</td>\n",
       "      <td id=\"T_1c241_row21_col25\" class=\"data row21 col25\" >6.23%</td>\n",
       "      <td id=\"T_1c241_row21_col26\" class=\"data row21 col26\" >7.25%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_1c241_row22_col0\" class=\"data row22 col0\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row22_col1\" class=\"data row22 col1\" >1.85%</td>\n",
       "      <td id=\"T_1c241_row22_col2\" class=\"data row22 col2\" >2.29%</td>\n",
       "      <td id=\"T_1c241_row22_col3\" class=\"data row22 col3\" >2.26%</td>\n",
       "      <td id=\"T_1c241_row22_col4\" class=\"data row22 col4\" >2.06%</td>\n",
       "      <td id=\"T_1c241_row22_col5\" class=\"data row22 col5\" >2.19%</td>\n",
       "      <td id=\"T_1c241_row22_col6\" class=\"data row22 col6\" >2.00%</td>\n",
       "      <td id=\"T_1c241_row22_col7\" class=\"data row22 col7\" >2.05%</td>\n",
       "      <td id=\"T_1c241_row22_col8\" class=\"data row22 col8\" >1.97%</td>\n",
       "      <td id=\"T_1c241_row22_col9\" class=\"data row22 col9\" >1.89%</td>\n",
       "      <td id=\"T_1c241_row22_col10\" class=\"data row22 col10\" >1.43%</td>\n",
       "      <td id=\"T_1c241_row22_col11\" class=\"data row22 col11\" >1.26%</td>\n",
       "      <td id=\"T_1c241_row22_col12\" class=\"data row22 col12\" >1.73%</td>\n",
       "      <td id=\"T_1c241_row22_col13\" class=\"data row22 col13\" >2.16%</td>\n",
       "      <td id=\"T_1c241_row22_col14\" class=\"data row22 col14\" >2.12%</td>\n",
       "      <td id=\"T_1c241_row22_col15\" class=\"data row22 col15\" >1.27%</td>\n",
       "      <td id=\"T_1c241_row22_col16\" class=\"data row22 col16\" >1.23%</td>\n",
       "      <td id=\"T_1c241_row22_col17\" class=\"data row22 col17\" >1.23%</td>\n",
       "      <td id=\"T_1c241_row22_col18\" class=\"data row22 col18\" >1.17%</td>\n",
       "      <td id=\"T_1c241_row22_col19\" class=\"data row22 col19\" >1.22%</td>\n",
       "      <td id=\"T_1c241_row22_col20\" class=\"data row22 col20\" >1.17%</td>\n",
       "      <td id=\"T_1c241_row22_col21\" class=\"data row22 col21\" >1.38%</td>\n",
       "      <td id=\"T_1c241_row22_col22\" class=\"data row22 col22\" >1.32%</td>\n",
       "      <td id=\"T_1c241_row22_col23\" class=\"data row22 col23\" >1.32%</td>\n",
       "      <td id=\"T_1c241_row22_col24\" class=\"data row22 col24\" >1.29%</td>\n",
       "      <td id=\"T_1c241_row22_col25\" class=\"data row22 col25\" >1.33%</td>\n",
       "      <td id=\"T_1c241_row22_col26\" class=\"data row22 col26\" >1.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_1c241_row23_col0\" class=\"data row23 col0\" >7.60%</td>\n",
       "      <td id=\"T_1c241_row23_col1\" class=\"data row23 col1\" >8.79%</td>\n",
       "      <td id=\"T_1c241_row23_col2\" class=\"data row23 col2\" >7.29%</td>\n",
       "      <td id=\"T_1c241_row23_col3\" class=\"data row23 col3\" >7.38%</td>\n",
       "      <td id=\"T_1c241_row23_col4\" class=\"data row23 col4\" >7.74%</td>\n",
       "      <td id=\"T_1c241_row23_col5\" class=\"data row23 col5\" >7.33%</td>\n",
       "      <td id=\"T_1c241_row23_col6\" class=\"data row23 col6\" >7.80%</td>\n",
       "      <td id=\"T_1c241_row23_col7\" class=\"data row23 col7\" >7.54%</td>\n",
       "      <td id=\"T_1c241_row23_col8\" class=\"data row23 col8\" >7.87%</td>\n",
       "      <td id=\"T_1c241_row23_col9\" class=\"data row23 col9\" >8.12%</td>\n",
       "      <td id=\"T_1c241_row23_col10\" class=\"data row23 col10\" >9.02%</td>\n",
       "      <td id=\"T_1c241_row23_col11\" class=\"data row23 col11\" >10.18%</td>\n",
       "      <td id=\"T_1c241_row23_col12\" class=\"data row23 col12\" >7.84%</td>\n",
       "      <td id=\"T_1c241_row23_col13\" class=\"data row23 col13\" >7.63%</td>\n",
       "      <td id=\"T_1c241_row23_col14\" class=\"data row23 col14\" >7.71%</td>\n",
       "      <td id=\"T_1c241_row23_col15\" class=\"data row23 col15\" >8.83%</td>\n",
       "      <td id=\"T_1c241_row23_col16\" class=\"data row23 col16\" >6.14%</td>\n",
       "      <td id=\"T_1c241_row23_col17\" class=\"data row23 col17\" >7.06%</td>\n",
       "      <td id=\"T_1c241_row23_col18\" class=\"data row23 col18\" >7.58%</td>\n",
       "      <td id=\"T_1c241_row23_col19\" class=\"data row23 col19\" >8.21%</td>\n",
       "      <td id=\"T_1c241_row23_col20\" class=\"data row23 col20\" >6.69%</td>\n",
       "      <td id=\"T_1c241_row23_col21\" class=\"data row23 col21\" >8.66%</td>\n",
       "      <td id=\"T_1c241_row23_col22\" class=\"data row23 col22\" >6.32%</td>\n",
       "      <td id=\"T_1c241_row23_col23\" class=\"data row23 col23\" >7.21%</td>\n",
       "      <td id=\"T_1c241_row23_col24\" class=\"data row23 col24\" >7.69%</td>\n",
       "      <td id=\"T_1c241_row23_col25\" class=\"data row23 col25\" >8.18%</td>\n",
       "      <td id=\"T_1c241_row23_col26\" class=\"data row23 col26\" >6.87%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_1c241_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_1c241_row24_col0\" class=\"data row24 col0\" >2.05%</td>\n",
       "      <td id=\"T_1c241_row24_col1\" class=\"data row24 col1\" >1.63%</td>\n",
       "      <td id=\"T_1c241_row24_col2\" class=\"data row24 col2\" >2.01%</td>\n",
       "      <td id=\"T_1c241_row24_col3\" class=\"data row24 col3\" >2.02%</td>\n",
       "      <td id=\"T_1c241_row24_col4\" class=\"data row24 col4\" >1.99%</td>\n",
       "      <td id=\"T_1c241_row24_col5\" class=\"data row24 col5\" >2.01%</td>\n",
       "      <td id=\"T_1c241_row24_col6\" class=\"data row24 col6\" >2.00%</td>\n",
       "      <td id=\"T_1c241_row24_col7\" class=\"data row24 col7\" >1.87%</td>\n",
       "      <td id=\"T_1c241_row24_col8\" class=\"data row24 col8\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row24_col9\" class=\"data row24 col9\" >1.95%</td>\n",
       "      <td id=\"T_1c241_row24_col10\" class=\"data row24 col10\" >1.85%</td>\n",
       "      <td id=\"T_1c241_row24_col11\" class=\"data row24 col11\" >1.65%</td>\n",
       "      <td id=\"T_1c241_row24_col12\" class=\"data row24 col12\" >2.04%</td>\n",
       "      <td id=\"T_1c241_row24_col13\" class=\"data row24 col13\" >2.03%</td>\n",
       "      <td id=\"T_1c241_row24_col14\" class=\"data row24 col14\" >2.07%</td>\n",
       "      <td id=\"T_1c241_row24_col15\" class=\"data row24 col15\" >1.55%</td>\n",
       "      <td id=\"T_1c241_row24_col16\" class=\"data row24 col16\" >1.71%</td>\n",
       "      <td id=\"T_1c241_row24_col17\" class=\"data row24 col17\" >1.97%</td>\n",
       "      <td id=\"T_1c241_row24_col18\" class=\"data row24 col18\" >1.70%</td>\n",
       "      <td id=\"T_1c241_row24_col19\" class=\"data row24 col19\" >1.67%</td>\n",
       "      <td id=\"T_1c241_row24_col20\" class=\"data row24 col20\" >1.78%</td>\n",
       "      <td id=\"T_1c241_row24_col21\" class=\"data row24 col21\" >1.68%</td>\n",
       "      <td id=\"T_1c241_row24_col22\" class=\"data row24 col22\" >1.71%</td>\n",
       "      <td id=\"T_1c241_row24_col23\" class=\"data row24 col23\" >1.93%</td>\n",
       "      <td id=\"T_1c241_row24_col24\" class=\"data row24 col24\" >1.74%</td>\n",
       "      <td id=\"T_1c241_row24_col25\" class=\"data row24 col25\" >1.75%</td>\n",
       "      <td id=\"T_1c241_row24_col26\" class=\"data row24 col26\" >1.79%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x308fe4290>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(16)\n",
    "fig.set_figheight(8)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot(kind='bar', width=0.8, ax=ax)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
